1. Field of the Invention
The present invention relates to a method and an apparatus for accurately detecting positions of eyes in an input face image, and more particularly, to a method and an apparatus for detecting eyes more promptly and reliably by removing restrictions for detection such as illumination, glasses and hair from an input face image, detecting available eye positions using a gradient descent method, and verifying the detected eye positions using an eye classifier which has obtained information from supervised learning using a learning algorithm.
2. Description of the Related Art
In general, eye detection used for security or user identification is divided into three operations; face detection, eye position extraction, and eye position verification.
For more reliable eye detection, face detection more than anything else has to be performed accurately. Specifically, the accuracy of face identification using all characteristic parts of a face depends on how accurately to detect a face region from an input image. Since recent face detection methods detect the face region very accurately, how accurately to detect eye coordinates from the face region is regarded as an important technical aspect.
Eye detection methods include a method of forming a projection profile on x and y axes of brightness in extracted eye regions and regarding the lowest values on the x and y axes as eye coordinates or a method of detecting eye positions from a plurality pairs of detected available eye positions using a template-matching method or geometric characteristics of the face image.
However, the method of forming a projection profile on x and y axes and detecting eye coordinates is sensitive to brightness of image pixels and cannot detect accurate eye coordinates easily due to hair or eyebrows included in a face image.
The method using a template-matching method is disadvantageous in that standardized eye templates can be varied in accordance with a database used for obtaining the templates and an eye detection rate is determined by a critical value set during binarization.